Agent-based processing and reasoning in embedded real-time environments depends on accurate and current data for responsiveness. However, frequent sensor readings or network requests for data may be undesirable due to energy or bandwidth costs, RF interference, stealth requirements, or other reasons. A problem to solve is how to balance agent/application needs for real-time responsiveness against the need to make infrequent sensor readings or network requests to fulfill other system requirements.
LEAP (Low Power Energy Aware Processing) is an example of a typical existing solution to monitor and control energy usage in embedded environments. LEAP enables applications to monitor and control energy usage on an individual node. However, it does not address the issue of agent/node responsiveness in real-time situations. A further problem with LEAP-type solutions is that they become unresponsive in time-critical situations when data is too old or unavailable, and they allow agents to make sensor observations or network requests without regard to energy/bandwidth costs or other issues.
What is required is a system and method for providing enhanced operation of a network of sensors.